docstr: Tests that the loss is always greater or equal to 0.0.
docstr_tok: ["Tests","that","the","loss","is","always","greater","or","equal","to","0.0","."]
code: def test_loss_positive(self, size):
      """Tests that the loss is always greater or equal to 0.0."""
      tensor_shape = np.random.randint(size, 6, size=3).tolist()
      image = tf.random.uniform(
          minval=0.0, maxval=1.0, shape=tensor_shape + [3]
      )
      matte = tf.random.uniform(
          minval=0.0, maxval=1.0, shape=tensor_shape + [1]
      )
  
      laplacian, _ = matting.build_matrices(image, size=size)
      loss = matting.loss(matte, laplacian)
  
      self.assertAllGreaterEqual(loss, 0.0)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_graphics.image import matting
  from tensorflow_graphics.util import asserts
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 16 for calling the MattingTest obj's underlying member method code with example usage: obj.test_loss_positive(size) without return types